Enhancing patient involvement in quality improvement: How complaint managers see their roles and limitations
Bibliographic record
Abstract
Patient involvement is a priority for healthcare organizations seeking to improve the quality of care and services. The contribution that complaint handling can make towards quality improvement has remained underexplored, while healthcare organizations are implementing strategies to effectively involve patients in quality improvement. We conducted a qualitative study to understand how complaint managers see their roles and limitations in enhancing patient involvement in quality improvement. A convenience sample of eleven complaint managers was selected from nine Canadian healthcare organizations with various annual volumes of complaints and situated in different settings (urban, rural, and semi-urban). The data were analyzed using a hybrid deductive-inductive approach with QDA Miner. The complaint managers saw themselves as having multiple roles that enhanced patient involvement in quality improvement: ensuring mediations with patients and clinical teams, monitoring improvements following a complaint, and informing the quality improvement and operations teams about the patients’ experiences. The complaint managers also reported limitations in their roles, such as the need to respect confidentiality that excluded patients from decisions about improvements and their hierarchical independence in the organization that kept them away from continuous quality improvement activities. Interestingly, the participants reported using new, promising practices that helped integrate, both retrospectively and proactively, the patients’ perspectives on quality improvement. Complaint handling can be effective, though it is a seldom-used gateway for integrating the patient’s voice in quality improvement. Several challenges need to be addressed to make complaint handling a more substantial element in the strategies for involving patients in healthcare organizations. Experience Framework This article is associated with the Quality & Clinical Excellence lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework) Access other PXJ articles related to this lens. Access other resources related to this lens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".